Package: matricks 0.8.2

matricks: Useful Tricks for Matrix Manipulation

Provides functions, which make matrix creation conciser (such as the core package's function m() for rowwise matrix definition or runifm() for random value matrices). Allows to set multiple matrix values at once, by using list of formulae. Provides additional matrix operators and dedicated plotting function.

Authors:Krzysztof Joachimiak [aut, cre]

matricks_0.8.2.tar.gz
matricks_0.8.2.zip(r-4.7)matricks_0.8.2.zip(r-4.6)matricks_0.8.2.zip(r-4.5)
matricks_0.8.2.tgz(r-4.6-x86_64)matricks_0.8.2.tgz(r-4.6-arm64)matricks_0.8.2.tgz(r-4.5-x86_64)matricks_0.8.2.tgz(r-4.5-arm64)
matricks_0.8.2.tar.gz(r-4.7-arm64)matricks_0.8.2.tar.gz(r-4.7-x86_64)matricks_0.8.2.tar.gz(r-4.6-arm64)matricks_0.8.2.tar.gz(r-4.6-x86_64)
matricks_0.8.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
matricks/json (API)
NEWS

# Install 'matricks' in R:
install.packages('matricks', repos = c('https://krzjoa.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/krzjoa/matricks/issues

Pkgdown/docs site:https://krzjoa.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

algebramatrixmatrix-manipulationcpp

4.68 score 4 stars 24 scripts 216 downloads 28 exports 23 dependencies

Last updated from:fd9987b6a4. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK138
linux-devel-x86_64OK145
source / vignettesOK203
linux-release-arm64OK136
linux-release-x86_64OK149
macos-release-arm64OK136
macos-release-x86_64OK214
macos-oldrel-arm64OK122
macos-oldrel-x86_64OK166
windows-develOK115
windows-releaseOK119
windows-oldrelOK127
wasm-releaseOK115

Exports:%-%%+%%d%%m%antidiagantidiag<-atat<-col_bindcrepis_idx_possiblemmatrix_idxneighbour_idxneighbour_idx_matrixonesplot_matrixrboolmrow_bindrreprunif_same_dimsrunifmseq_matrixset_valuessvvwith_same_dimszeros

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemagrittrplyrR6RColorBrewerRcppreshape2rlangS7scalesstringistringrvctrsviridisLitewithr

Use case: Iterative Policy Evaluation (Reinforcement Learning)

Rendered frompolicy_evaluation.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2020-02-01
Started: 2020-01-06